Asset and liability modeling tool

ABSTRACT

A method for modeling financial variables describing a client over a time period. The method may comprise the step of generating a first simulation of the time period. Generating the first simulation may comprise the steps of assigning the client to a first health-related state and advancing the first simulation from a first interval of the time period to a second interval of the time period. A probability that the client will transition from the first health-related state to a second health-related state may be calculated, the client may be randomly assigned to either the first health-related state or the second health-related state considering the probability. According to various embodiments, the methods may also comprise the steps of calculating a client income for the second interval; and calculating a plurality of client expenses for the second interval. Also, the various health-related states may include one or more of a healthy state, a long term care (LTC) state, a disabled state and a dead state.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No. 12/804,013, filed Jul. 12, 2010, which is a continuation of U.S. application Ser. No. 11/784,968, filed on Apr. 10, 2007, which is a continuation-in-part of U.S. application Ser. No. 11/389,962 filed on Mar. 27, 2006, the entire contents of each of which being fully incorporated herein by reference.

STATEMENT UNDER 37 C.F.R. §1.84(a)(2)

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.

BACKGROUND OF THE INVENTION

There is a present need in asset management to move towards “liability-led investing” at the individual and/or household level. Currently, there is an observable trend for governments and corporations to push the responsibility for pension and healthcare liability management and financing back to the individual because existing arrangements for their funding are either unaffordable or the financing risk is too high. Consequently, it has become increasingly important for individuals to accurately model their financial condition into the future in order to plan for multiple goals such as retirement, college education for children, etc.

Such modeling is a challenging task. Most individuals have multiple future goals, some flexibility in the timing and acceptable spend of those future goals (e.g., they can retire earlier or later; retire on a higher or lower retirement income) and dynamic goal priorities (e.g., will trade-off goals differently depending on the likely level of spend). Dependencies between these goals go forwards and backwards in time. For example, if an individual (or household) spends more on their children's education, he or she will have less to support retirement. On the other hand, if the individual retires later, he or she may be able to afford to spend more on their children's education today.

On top of this wide array of goals and related choices, individuals (and households) face uncertainty about their future income, future expenses, and even how long they are going to live. For example, there is uncertainty about an individual's future earned income, social security receipts, Medicare benefits and returns on their savings and investments. There is also uncertainty about an individual's future expenditures on healthcare, nursing care, residential care, etc. There is a risk the individual may die young. Under those circumstances, they want to be sure their family is provided for. There is also a risk the individual may live a long time. In that case, they want to be sure that they have enough assets to support them through a very long retirement, where healthcare costs may be high.

When considering assets, liabilities, goals, and the uncertainties of life, people care about every outcome. There are, however, too many variables for any individual, no matter how intelligent, to solve the problem in all of its complexities and find comprehensive answers. Most individuals solve the problem serially. For example, if they have enough money, they will send their children to a particular school without a thorough understanding of how that would affect their retirement age or spend, or how it would impact their family if they were to die unexpectedly.

There are existing tools for modeling an individual's financial situation, however, they do not fully address the problem. In general, existing tools focus on funding individual goals and ignore the interactions and time dependencies between cashflows and their priorities. They ignore unforeseen events such as health events or the need for long-term care. These existing tools assume that the only risk decision to be made by the individual is how much risk to take in the investment portfolio. They therefore focus the individual on expected portfolio returns, or the degree of investment risk needed to meet that single goal. They do not help the individual assess the nature of the risks to their meeting their set of goals, nor help them understand the nature and consequences of the choices they have, of which investment risk is but one.

BRIEF SUMMARY OF THE INVENTION

In one general aspect, the present invention is directed to a method for displaying the results of a financial model to allow visual assessment of a client's future financial condition in an interactive, timely content-rich manner. The financial model may be generated by a financial modeling tool that captures a comprehensive set of future financial variables for the individual (e.g., cashflows, liabilities etc.), and the uncertainty and range of possible outcomes for each. The financial model is displayed in a manner that provides a way of visualizing the possible outcomes that enable the individual to understand that range, and understand the consequences on the outcomes of different choices they have. In so doing, the model may focus individuals on risk management with respect to their future goals, not simply on investment returns. In addition, the financial model, in various embodiments, may make financial advising more attractive to individuals by allowing for the generation of an approximate model based on abbreviated input data, for example, a set of input data that may be entered on a single screen. The abbreviated input model enables the individual to provide accurate input data whilst engaged in reviewing the results, as opposed to providing comprehensive input data prior to reviewing the output. This may provide an incentive for individuals to engage in the often complex and time consuming process of creating a full financial model.

The financial model models the client's future financial condition over a given time period (e.g., a life, the life of a household, etc.) by generating a likely range of forecasted values over the time period for one or more financial variables describing the client. Exemplary financial variables include, net worth, liquid assets, investable assets, outflow, annual cashflow, available net worth (i.e., balance sheet and cashflow items), etc. In various embodiments, the financial model may include a number of computer simulations of the time period. Each computer simulation may generate a set of possible forecasted values for the financial variable or variables over the time period. The aggregate of the sets of values from all of the simulations forms the results of the financial model (e.g., a distribution of possible outcomes for the client).

The results of the financial model may be displayed as a graphical representation, which may display results for some or all of the modeled financial variables so that the client can gain a visual understanding of their prospective financial condition and gain insight as to the consequences of different available choices. The graphical representation may take the form of a topographical chart positioned on a plane defined by a time axis and a value axis, such that values of the financial variables over time may be plotted on the time and value axis. Each coordinate set on the axes may correspond to a point on the topographical chart. The height of the points on the topographical chart indicates the likelihood that the displayed financial variable will take the value and time indicated by the corresponding coordinate sets. For example, the height of the points may indicate the number of simulations that result in a value and time of the displayed financial variable or variables represented by the corresponding coordinate set. In various embodiments, the color of points on the topographical chart also indicates the likelihood that the displayed financial variable will take the value and time of the corresponding coordinate sets (e.g., how many of the simulations result in the corresponding coordinate sets). For example, more intense colors may indicate a larger portion of the simulations. In that way, the height, color, and intensity of points on the topographical chart may be indicative of the probability that the forecasted variables will have the value and time of the corresponding coordinate sets. The color of points on the topographical chart may also indicate whether the represented value of the financial variable is positive or negative. For example, negative values of the financial variable or variables (e.g., values indicating that the client will lack financial means) may be red while positive values may be green.

The graphical representation may also comprise representations of one or more goals of the client at a point or points in time. Each goal may represent an expenditure or other financial event that the client would like to achieve in the future. Each representation indicates a portion of the simulations where the goal is achieved. Also, selecting the representation of the goal may allow detailed information about the goal to be viewed and/or edited. Where the goal is a retirement goal, the time after retirement may be partitioned into a plurality of time blocks. The success of the retirement goal, (e.g., whether the client has enough assets and/or income to meet desired consumption levels) may be indicated for each time block. The user may be able to drag a goal on the topographical chart so as to adjust the time horizon for the goal. The simulations may be accordingly regenerated to determine the likelihood of achieving the goal given the revised horizon. The user may also be able to analyze the graphical representation. For example, placing a cursor over the representation at various points in time may display information over the various simulations (e.g., the distribution of possible outcomes at that point in time, states of the client, etc.) In various embodiments, the user may manipulate the viewing angle of the graphical representation using navigation buttons.

In another general aspect, the present invention may be directed to a method for modeling financial variables describing a client over a time period. The method may comprise the step of generating a first simulation of the time period. Generating the first simulation may comprise the steps of assigning the client to a first health-related state and advancing the first simulation from a first interval of the time period to a second interval of the time period. A probability that the client will transition from the first health-related state to a second health-related state may be calculated, the client may be randomly assigned to either the first health-related state or the second health-related state considering the probability. According to various embodiments, the methods may also comprise the steps of calculating a client income for the second interval; and calculating a plurality of client expenses for the second interval. Also, the various health-related states may include one or more of a healthy state, a long term care (LTC) state, a disabled state and a dead state.

In yet another general aspect, the present invention may be directed to methods of simulating the finances of a client over a time period. The methods may comprise the step of receiving a description of a first goal. The description of the first goal may comprise a priority of the first goal, a date for the first goal, a minimum amount for the first goal and a desired amount for the first goal. The methods may also comprise the step of receiving a description of a second goal, which may also comprise a date for the second goal, a minimum amount for the first goal a desired amount for the second goal, and a priority of the second goal, which may be lower than that of the first goal. The client income and expenses over a first interval of the time period may be calculated, with the client expenses categorized into discretionary and non-discretionary expenses. The non-discretionary expenses may be funded with at least a portion of the client income. If any client income remains, at least a portion of the remaining client income may be allocated to a first goal account and a second goal account. This allocating may comprise the steps of assigning a minimum amount to the first goal account; if any client income remains, assigning a minimum amount to the second goal account; and if any client income remains, assigning a desired amount to the first goal account.

The user of the financial modeling tool may be the client itself (e.g., a business entity, individual, or household), or in various embodiments, may be a financial advisor or other representative working on behalf of the client.

BRIEF DESCRIPTION OF THE FIGURES

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. Embodiments of the present invention are described herein, by way of example, in conjunction with the following figures, wherein:

FIG. 1 shows a block diagram of a system for implementing a financial modeling tool;

FIG. 1A shows an exemplary workflow for use with a financial modeling tool;

FIGS. 2-46 depict screen shots of user interfaces provided by a financial modeling tool according to various embodiments of the present invention;

FIG. 47 shows an exemplary process flow for use with a financial modeling tool; and

FIGS. 48 and 49 show exemplary state diagrams for use with a financial modeling tool.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention are directed in general to a financial modeling software tool that allows a user to generate a financial model of the possible future financial condition of an individual or household (e.g., a client) based on current data and assumptions about the future. The financial model models the clients' future financial condition by forecasting the values of one or more financial variables such as, for example, net worth, liquid assets, investable assets, outflow, annual cashflow, available net worth, etc. The model may be generated using any suitable modeling method or methods for simulating asset returns and stochastic liabilities (e.g., a Monte Carlo method) and may be based on input data and assumptions specific to the client. Results of the model may be presented to a user of the financial modeling tool and/or clients in a visual, interactive and content-rich manner. For example, the results may be displayed on a topographical chart, as shown in FIG. 32, where the height of each point on the chart indicates the probability that a displayed financial variable or variables will have the value and time indicated by coordinates of the point (e.g., the height at a point corresponding to a million dollars at a given time in the future may indicate the likelihood that the client's net worth will be one million dollars at the given time). Before detailing screen shots of an exemplary user interface allowing the user to input data and set future assumptions, and before detailing the visual, interactive output, a few words are needed about the environment and workflow in which the system may be used.

FIG. 1 shows a diagram of a computer system 110 for implementing a financial modeling software tool 100 according to various embodiments of the present invention. The system 110 includes a server 106 in communication with one or more user machines 102 via a network 104, which may be any suitable wired or wireless communication network including, for example, a LAN or a WAN. The financial modeling tool 100, may be a software program executed by the server 106, and may include a plan module 108 and a simulation module 112. The plan module 108 may provide one or more user interfaces that allow a user of the tool 100 to enter input data that is used as input to develop the model. In various embodiments, the plan module 108 may provide the user interfaces to the user machines 102, prompting the user to enter the input information, for example, interfaces 600, 300, and 700 described below.

Various input data for developing the model may be stored in databases 114, 116, 118, 120. The input data may be received from a user, for example, via plan module 108, or may be received from an outside source, such as a subscription service, etc. Plan database 118 may store financial information about the client including, for example, income, asset, and liability information. The plan database 118 may also store goal information for the client, as described in more detail below. In various embodiments, the plan database 118 may include data about a client entered through the plan module 108 in a current or previous session, as well as generic or stock data that may be applied to multiple clients. Assumption database 116 may include data describing assumptions that may be used when developing the model. Exemplary assumption data includes, the loss tolerance of the client (e.g., the client's tolerance for one year losses on their investment portfolio), the tax status of the client, the transaction costs for buying and selling assets, etc. Other examples of assumption data may include actuary tables or other data for modeling states of the client (e.g., date of death, disability state, etc.). Assumption data may be entered through the plan module 108 or may be default data that may be applied to multiple clients, such as, for example, default transaction costs, default retirement consumption adjustments, etc.

An economic database 114 may include data describing historical economic performance that may be considered in generating the model. For example, the database 114 may include data describing the historic trends of the stock market, interest rates and the related expected asset returns, volatilities and covariances, etc. Regulation database 120 may include information describing various laws and regulations that may affect the model including, for example, tax codes, securities laws and regulations, etc. Data stored at the economic and regulation databases 114, 120 may be received from one or more data subscription services.

The simulation module 112 may model the possible range of the client's forecasted financial condition over the chosen time period considering the input data stored in databases 114, 116, 118, 120. The time period may be, for example, the client's expected life. In various embodiments, the simulation module 112 may model the range of the client's forecasted financial condition according to a Monte Carlo technique, for example, by simulating both asset returns and stochastic liabilities, in the context of desired future cashflows (e.g., the amounts required for the client to meet future goals and expenses). For each simulation, the simulation module 112 may generate output values for the financial variables over one instance of the time period, considering the input data, assumptions and other constraints.

In various embodiments, each simulation may generate values of the financial variables based on assumptions regarding states of the client, and/or the economy at large. For example, each simulation may generate a date of the client's death; whether and, if so, when the client experiences a disability; whether and, if so, when the client requires long term care; etc. Each simulation may also assume future economic trends regarding, for example, the stock market, interest rates, etc. The states assumed by any particular simulation may be randomly generated, but based on the likelihood of the states occurring, for example, as shown by actuary tables, assumptions, or other input data/constraints. For example, if the statistical data indicates that there is a 5% chance that the client will experience a disability at age 40 and a 10% chance that the client will experience a disability at age 50, then approximately 5% of the total number of simulations may assume a disability at age 40 and approximately 10% will assume a disability at age 50.

It will be appreciated that, in various embodiments, the values for the financial variables generated during each simulation may reflect the dependency and/or covariance of the financial variables on each other. For example, the values for asset returns, interest rates and inflation rates generated by any given simulation may allow for the historic co-variance of those variables. Also, the simulations may generate values of future earned income that covary with the financial variables representing economic state and inflation rates. In addition, each simulation may model actuarial co-variances (e.g., a different likelihood of needing long-term care if disabled; different life expectancy depending on health status).

The aggregate of the sets of values from all of the simulations may be displayed to the user and/or the client as a topographical chart or other graphical representation, for example, shown by user interfaces 900 and 1000 of FIGS. 32-46 and described in more detail below. The topographical chart may show results for one financial variable at a time, or may show results for numerous financial variables simultaneously.

It will be appreciated that in various embodiments, some or all of the software program of the financial modeling tool 100 may be executed by components of the network 110 other than the server 106. For example, user machines 102 may contain some or all of the software of the financial modeling tool 100. In such embodiments, the user machines 102 may access the databases 114, 116, 118, 120 via server 106, or may, in various embodiments, each include local copies of the databases 114, 116, 118, 120. It will also be appreciated that the databases 114, 116, 118, 120 may be implemented using any number of physical or logical storage devices.

FIG. 1A shows an exemplary workflow 200 of the financial modeling tool 100 according to various embodiments. At box 202, the tool 100 may receive information about the client that will be the subject of the model. The information may include information about an individual client, or information about the client's household including, for example, a spouse or other co-client and children. An exemplary user interface 600 for receiving the client information is shown in FIGS. 2-5 as described below.

From step 202, the client, and/or the user of the financial modeling tool 100, may choose to enter an abbreviated plan at box 204 or a full plan at box 206. Entering a full plan at box 206 may include entering detailed plan and assumption information about the client including the client's income, assets, liabilities, goals, etc., for example, at user interface 700 shown at FIGS. 7-31. It will be appreciated that entering a full plan may be complex and time consuming. Accordingly, the client and/or user may alternatively enter an abbreviated plan at box 204 that may include less information or less detailed information about the client than is entered in a full plan. An exemplary user interface 300 for receiving an abbreviated plan is shown below in FIG. 5. When an abbreviated plan is received, data for generating the outcomes may be collected from the client in a single screen, rather than requiring the user to enter information at multiple screens. The plan module 108 and/or the simulation module 112 may supplement the abbreviated plan by estimating additional information needed to run the simulations.

At step 208, the simulation module 112 may run one or a series of simulations of the client's life based on the information received at steps 202, 204 and/or 206. Results of the simulations may be displayed at box 210, for example, as one or more of the graphical representations shown at interface 900 in FIGS. 32-46. It will be appreciated that simulations run based on full plans may generate more accurate results than those run based on abbreviated plans. It will also be appreciated that even some full plans can be made to result in more accurate simulations by entering additional and/or more accurate information. For example, if the client and/or user enters a full plan at box 206, but does not enter a particular set of assets, then the accuracy of the resulting simulations will suffer. Accordingly, when the results of the simulations are shown at box 210, the user and/or client may have the option of creating or supplementing a full plan at box 206. The new full plan may then be used by the simulation module 112 to generate more accurate simulations.

Clients are sometimes reluctant to enter or provide a user (e.g., a financial analyst) with enough financial and/or personal information for the simulation module 112 to generate its most accurate simulations. For one thing, gathering and entering the sheer volume of desirable information may take a long time. For another, the client may be hesitant to provide detailed information to a financial analyst with whom they may not have an established relationship, or who may not manage all of their assets. Accordingly, the financial modeling tool 100 may be used to motivate the client to disclose and/or enter as much information as possible. For example, the client may enter and/or disclose to a user only the information necessary for an abbreviated plan. Based on the outcomes of the simulations from the abbreviated plan, however, the client may become quickly engaged by the resulting graphical representation of the output and may be more motivated to provide additional and/or more accurate information as required to further understand the impacts on the output. It will be appreciated that subsequent outputs and graphical representations based on the additional and/or more accurate information may themselves be more accurate. The client and/or the user may then begin to create or supplement a full plan by entering the additional data and re-running the financial model. In this way, the financial modeling tool 100 may move away from the linear logic of requiring a client to provide and/or enter all input information before the client can become engaged in the model's output.

FIGS. 2-31 show embodiments of user interfaces 600, 300, 700 that may be provided to the user, for example, by the plan module 108 according to various embodiments to allow the user, at user machine 102, to enter input data about the client's assets and liabilities as well as future goals and other assumptions and constraints regarding the future. The input data entered through the user interfaces may then be considered by the simulation module 112 to generate models of the client's future financial condition, as discussed herein. Each of the interfaces 600, 300, 700 includes a navigation toolbar 602 and navigation buttons 612, 614 that may allow the user to navigate between the various screens. Toolbar 602 includes buttons or tabs that may allow the user to jump between various screens of the interfaces 600, 300, and 700. It will be appreciated that various interfaces 600, 300, 700 or screens therein may not function until prerequisite information has been entered at another screen and/or prerequisite calculations have been performed. For example, it may not be possible to enter a qualified employee contribution income type, as shown at FIG. 15, until a qualified asset has been added to receive the contribution, as shown at FIG. 9.

FIGS. 2-4 show embodiments of the user interface 600, according to various embodiments that may be provided to the user, for example, to prompt the user to enter and/or edit information about the client who will be the subject of the financial modeling tool 100. Again, as mentioned above, the user may be the client itself, or may be a financial advisor or some other representative of the client. The interface 600 includes an additional toolbar 604 having buttons or tabs 605, 607, 609 corresponding to different screens within the user interface 600. Selecting one of the buttons or tabs 605, 607, 609 causes the corresponding screen to appear. In FIG. 2, the Select Client button 605 has been selected, allowing the user to select an existing client, or create a new client. Field 608 allows the user to search existing clients by various criteria including, for example, recently accessed clients, office and financial analyst identifiers, names, household names, etc. The results of the search performed at field 608 may be shown at field 610. The user may select an existing client from field 610, or in various embodiments, may select an entry allowing the user to create a new client. Data about existing clients may be stored, for example, in plan database 118.

FIG. 3 shows the interface 600, according to various embodiments, with the Select Household button 607 selected. The financial modeling tool 100 may receive information regarding all members of the client's household. Household members presently associated with the selected client's household may be listed at field 618. For example, in the non-limiting embodiment shown in FIG. 3, the selected client's household includes the client, the client's spouse, and one dependent child. Selecting a particular household member from field 618 may enable detailed information corresponding to the selected household member to be entered and/or viewed at field 620. Additional household members may be added, or existing household members deleted, using field 616 and add/remove buttons 621, 623. Field 616 includes representations of various kinds of household members including, for example, a client 622, a co-client 624 (e.g., a spouse) and a dependent 626. Selecting one of the representations 622, 624, 626 and then selecting the add button 621 may add an instance of the selected type of household member to field 618. Likewise, selecting a household member from field 618 and then selecting the remove button 623 may remove that member from the selected client's household. Household members may also be added or removed from the client's household by selecting the appropriate icon and dragging it to or from field 618.

FIG. 4 shows the interface 600, according to various embodiments, with the Select Scenario button 609 selected. The client may be listed at field 630, and other members of the client's household may be listed at field 632. The user may select a plan for the client from field 634. The field 634 may include representations of various pre-existing plans 636, 637, which may be stored in database 118. The pre-existing plans may be plans generated for the client in an earlier session, or may be stock or example plans. Pre-existing plans may be stored, for example, at plan database 118. The user may select a currently loaded plan (e.g., if a plan is currently loaded) by choosing icon 633. Selecting a pre-existing plan 636, 637 or currently loaded plan 633 from field 634 may cause additional details of the plan to appear at plan preview field 638. The additional details may include the client's name, the other members of the client's household, the client's assets/liabilities, the client's goals, etc.

New plans may be generated by selecting one of the icons 631 and 635. The user may have the option to create and/or use a full plan by selecting icon 635 or an abbreviated plan by selecting icon 631. As described above, a full plan allows the user to enter detailed plan and assumption information about the client including the client's income, assets, liabilities, goals, etc. This information is then considered by the simulation module 112 in generating a model of the client's future financial condition. An abbreviated plan allows the user to enter less detailed financial information about the client, which may require substantially less time and effort. In various embodiments, data for the abbreviated plan may be entered in a single user interface screen such as, for example, user interface 300 shown in FIG. 5. The plan module 108 and/or the simulation module 112 then considers this less detailed information and may estimate additional information needed to generate the output. It will be appreciated that simulations run according to full plans may generate more accurate results than those run according to abbreviated plans. Seeing an output generated according to an abbreviated plan, however, may encourage the client to complete a full detailed plan by showing the client the impact of more precise data on the distribution of outputs.

FIG. 5 shows an embodiment of a user interface 300, according to various embodiments, that may be provided to the user by the plan module 108 for receiving an abbreviated plan. The interface 300 includes a field 302 that allows the user to view and/or edit information relating to the client's income, expenses, and assets. Income items entered may include pre-retirement earned income and post-retirement earned income. Also, various asset types and values may be viewed and/or edited at field 302, such as, for example, qualified and non-qualified assets. The interface 300 also includes a real estate and mortgage field 304. The field 304 may allow the user to view and/or edit information about the client's real estate and any mortgage or mortgages on the real estate. Additional instances of real estate may be added by selecting box 308. The client's financial goals may be viewed and/or edited at field 306. Field 306 shows two goals, 314 and 316. Each goal may include a goal type, a start date, a duration, a minimum value, and a desirable value. The goals' type may be modified using drop-down window 313. Exemplary goal types include home purchase, college education, pre-college education, wedding, major purchase, etc. Additional goals may be added by selecting button 310. When appropriate information is entered at fields 302, 304 and 306, the user may select the Simulate button 312, causing the simulation module 112 to generate a model based at least in part on the information entered at interface 300.

FIGS. 6-30 show embodiments of a user interface 700, according to various embodiments, that may be provided to the user according to the plan module 108 for receiving a full plan. Like the interface 600, the interface 700 may include navigation toolbar 602 and navigation buttons 612, 614 for allowing the user to navigate between various screens of the user interfaces. The interface 700 may also include navigation toolbar 704 having buttons 705, 707, 709, 711, 713, 715, 717, 719, 721, with each button corresponding to one or more screens included in the user interface 700.

FIG. 6 shows the interface 700, according to various embodiments, with the Scenario Overview button 705 selected. Field 706 may allow the user to view and/or edit plan (e.g., scenario) details including, a plan name, plan creation date, plan calculation date, etc. In various embodiments, the user may also be able to edit other information at field 706 including, for example, the loss tolerance of the client (e.g., the tolerance of the client for one year losses in their investment portfolio). Field 708 may also allow the user to view and/or edit the client's address. In embodiments where the user is acting on behalf of the client, a field 710 (shown in FIG. 6A) may list information about the user including, for example, their name and other identifying information (e.g., a financial analyst number, a branch number, etc.).

FIG. 7 shows the interface 700, according to various embodiments, with the People button 707 selected. This screen may allow the user to view and/or edit the members of the client's plan. The members of the client's plan may, or may not, be identical to the members of the client's household selected above with reference to interface 600. Referring back to FIG. 7, the current members of the client's plan may be listed in field 714, with detailed information about the selected plan member listed in field 716. Additional members may be added to the plan by selecting a member type from field 712 and using add/remove buttons 718 or by selecting the icon or representation of the member type and dragging it to field 714. Also, a plan member may be removed by selecting the icon for the plan member in field 714 and using add/remove buttons 718 or dragging the icon from field 714.

FIGS. 8-12 shows the interface 700, according to various embodiments, with the Assets button 709 selected. Icons representative of the various types of asset classes that may be held by the client are shown in field 720. Field 720 shows exemplary classes including, non-qualified, qualified, real estate, and physical assets. It will be appreciated, though, that in other embodiments, different asset classes may be used. Each asset class may have an associated tab 724, 726, 728, 730 in field 722. The user may access the tab by selecting it, or by selecting the representation of the associated asset class from field 720. Selecting the applicable tab 724, 726, 278, 730 allows data about the corresponding asset to be entered, as shown below.

In FIG. 8, field 722 is shown displaying tab 724, corresponding to financial non-qualified assets. Financial non-qualified assets may include assets held in accounts that do not meet treasury code requirements and therefore do not receive favorable tax treatment. The tax treatment status of the assets may be used by the simulation module 112 when generating the model. The user may view and/or enter information about specific non-qualified assets held by the client at field 732. For example, the asset type, asset owner, purchase date, purchase price, market value, etc., may be shown. The user may add an additional non-qualified asset by selecting the button 734 and entering the relevant information in field 732. In various non-limiting embodiments, the user may also add an additional non-qualified asset by selecting the non-qualified asset representation or icon from field 720.

FIG. 9 shows the field 722, according to various embodiments, with the Financial Qualified Assets tab 726 selected. Financial qualified assets are the opposite of non-qualified assets and may include assets held in accounts that do meet treasury code requirements to receive favorable tax treatment, such as, for example, section 401k accounts, Individual Retirement Accounts (IRA's), etc. In some jurisdictions, there may be restrictions on the liquidity of qualified assets prior to retirement without significant financial penalty. The user may enter and/or view various information regarding financial qualified assets held by the client at field 736. For example, the asset class, account classification, owner, and market value of each asset may be listed. New financial qualified assets may be added by selecting the button 740 and/or by selecting the icon of the financial qualified asset at field 720.

FIG. 10 shows the field 722, according to various embodiments, with the Real Estate tab 728 selected. The user may enter and/or view various information regarding real estate assets held by the client at fields 744 and 746. Field 744 may include a representation of each real estate asset held by the client. Selecting the representation of a real estate asset shown at field 744 may allow detailed information about the selected asset to be shown and/or edited at field 746. The detailed information may include a description of the asset, the owner of the asset, the state where the asset is located, purchase information regarding the asset, market value of the asset, and information regarding any mortgages on the asset as shown in FIG. 10 and in more detail in FIG. 11. Additional real estate assets may be added to or removed from field 744 by selecting the representation of a real estate asset in field 720 and selecting the appropriate button from field 742. Again, this information, such as the mortgage amount, term and interest rate may be used by the simulation module 112 when it generates the model of the client's future financial condition.

FIG. 12 shows the field 722, according to various embodiments, with the Physical Asset tab 730 selected. The user may enter and/or view various information about physical assets held by the client at fields 748 and 750. The assets listed under tab 730 may be non-real estate physical assets including, for example, cars, boats, jewelry, electronic equipment, etc. Representations of the physical assets owned by the client may be listed at field 748. The user may add an asset to field 748 by selecting the physical asset icon from field 720 and either using add/remove buttons 742, or dragging the icon to field 748. Doing so may cause field 751 to appear, as shown in FIG. 12A, allowing the user to choose the appropriate class of a physical asset. Also, selecting a physical asset representation from field 748 may allow detailed information regarding the asset to be reviewed and/or edited at field 750. Again, physical assets may be removed from field 748 using add/remove button pair 742, or by selecting the icon of the appropriate asset from 748 and dragging it away.

FIGS. 13-15 show the interface 700, according to various embodiments, with the Income button 711 selected. Representations of the types of income that may be received by the client are shown in field 752. Non-limiting examples of income types include salary or earned income, non-salaried income, and qualified employer contributions. Fields 754 and 764 may allow the user to view or edit additional information about examples of each class of income. For example, each class of income may have an associated tab at field 754. Selecting the tab associated with an income class, or selecting the representation of the income class from field 752 may cause field 754 to list the currently entered incomes of the client.

In FIG. 13, fields 754 and 764 are shown, according to various embodiments, with the Salary Income tab 758 selected. Representations or icons of the items of salary income directed to the client or other members of the client's household are shown at field 754. Selecting a representation may allow detailed information about the income to be displayed and/or edited at field 764. For example, owner, amount, start date, end date, and growth rate options are shown at field 764. Additional items of salary income may be added to or removed from field 754 by using the add/remove buttons 756 or by using the select and drag method discussed above. For example, the user may select the representation for salary from field 352 and drag it to field 754 or use add remove buttons 756.

FIG. 14 shows the fields 754 and 764, according to various embodiments, with the non-salaried income tab 760 selected. Representations of instances of Non-Salaried Income directed to the client or other members of the client's household are shown in field 754. Examples of non-salaried income may include social security, alimony, rent income, fixed annuities, child support, defined benefit pensions, etc. Selecting the representation of an instance of non-salaried income from field 754 may allow detailed information about the instance to be viewed and/or edited at field 764. Instances of non-salaried income may be added or removed to field 754 using add/remove buttons 756.

FIG. 15 shows the fields 754 and 764, according to various embodiments, with the Qualified Employer Contributions tab 762 selected. Representations of qualified employer contributions directed to the client or members of the client's household are listed at field 754. Selecting the representation of a particular instance may allow detailed information about the qualified employer contribution to be listed at field 764. Exemplary detailed information may include the owner of the income, the employee contribution required, the employer matching percentage and maximum contribution as well as whether and how much the employee contribution and employer maximum contribution will grow. For example, the growth information may be entered at drop down field 765. The user may select various growth rates including, for example, the Global CPI rate, or no growth at all. Instances of qualified employer contributions may be added or removed using add/remove buttons 756, or by the selecting and dragging method described above. It will be appreciated that the user may not be able to enter or edit any instances of qualified employer contributions unless the client owns qualified assets, for example, as described, at tab 726 of FIG. 9. Also, for example, the qualified employer contribution data inputs may be constrained by applicable regulatory provisions which may be stored, for example, at regulation database 120.

FIG. 16 shows the interface 700, according to various embodiments, with the Expenses button 713 selected. In the non-limiting embodiment shown in FIG. 16, the interface 700 is organized into a series of columns and rows. An expense column 766 lists expense categories in a nested format. For example, clicking on the [+] icon next to a category may cause sub-categories under the selected category to appear. Accordingly, the client's expenses may be considered at a broad level, a detailed sub-category level, or a combination of both. Exemplary categories include, for example, Taxes, Pets, Lifestyle, Insurance Premiums, Household Food, Childcare, Auto, Additional Healthcare, etc.

For each category and sub-category listed in expense column 766 corresponding entries may exist in the minimum amount column 768 and the maximum amount column 770. The user may list the minimum and maximum amounts that the client expects to spend on a particular category in its corresponding entries in columns 768 and 770, respectively. In that way, the client's expenses can be bracketed between expected minimum and maximum amounts. It will be appreciated that, in various embodiments, the user may forgo entering values for all sub-categories and may instead enter minimum and maximum amounts only for total annual expenses 773, 775 and/or a portion of the categories.

Each of the columns 768 and 770 may include a respective Other item 769, 771. The Other items 769, 771 may allow a user to categorize some, but not all, of the client's expenses under one or more of the nested categories discussed above. For example, the Other items 769, 771 may display the difference between the total annual expenses 773, 775 of the client and the sum of the amounts classified in the respective categories. For example, referring to Other item 769, if the minimum amount of total household expenses is $25,000 and no other expenses are categorized, then, the amount of the Other item 769 would be $25,000 so that the total minimum annual expenses value 773 would remain at $50,000. As the sum of the categorized expenses increases (e.g., as more expenses are categorized), the value of the Other item 769 decreases until the sum of the categorized expenses equals the total minimum annual expenses 773. At that point, if the sum of the categorized expenses were to increase further, the Other item 769 would remain at zero and the total expenses 773 would increase. It will be appreciated that the categorized expenses, Other item 771 and total maximum annual expenses 775 of Maximum Amount column 770 may behave in a similar manner.

FIGS. 17-18 show the interface 700, according to various embodiments, with the Loans button 715 selected. Representations of different classes of loans are listed in field 772. Example loan classes include mortgage, home equity, margin loans, qualified account loans, etc. Fields 776 and 782 may show information about loans of different classes held by the client. Field 776 may include tabs 778, 780, with each tab corresponding to one or more classes of loans. The user may access the tabs 778, 780 by selecting them, by selecting a representation of a corresponding loan class listed under the tab from field 772, or by selecting the representation of the corresponding loan class from field 772 and dragging it to field 776. As mentioned above, the amount, term, and rates of the client's various loans may be considered by the simulation module 112 in forecasting the client's future financial condition.

FIG. 17 shows fields 776 and 782, according to various embodiments, with the Mortgages tab 778 selected. The field 776 includes representations of mortgage-type loans held by the client. Selecting one of the representations of the mortgage-type loans in field 776 allows detailed information about the selected mortgage-type loan to be edited and/or viewed at field 782. For a mortgage-type loan, the detailed information may include the underlying property, the outstanding loan amount, the mortgage type, the annual interest rate, the term, etc. One or more additional mortgages may be added to the field 776 by selecting the mortgage representation from field 772 and using the add/remove buttons 774, or selecting and dragging the representation to field 776. A mortgage may similarly be removed from field 772 by selecting the representation or icon of the mortgage to be removed and using the add/remove buttons 774.

In various embodiments, the field 776 may be pre-populated to include mortgages relating to real property described, for example, at tab 728 shown in FIG. 10.

FIG. 18 shows the fields 776 and 782, according to various embodiments, with the Other Loans tab 780 selected. The field 776 includes representations of other, non-mortgage loans held by the client. For example, in FIG. 18, field 776 includes a home equity loan. Detailed information about a loan may be viewed and/or edited at field 782 by selecting the representation of the loan from field 776. Loans may be added or removed from field 776, for example, in the manner described above with respect to tab 778. Some or all of the information relating to the home equity loan may be pre-populated based on mortgages already existing on the client's real property.

FIG. 19 shows the interface 700, according to various embodiments, with the Insurance button 717 selected. Field 784 includes representations of exemplary classes of insurance. Indicators of insurance policies actually held by the client are shown in field 785. Selecting one of the indicators in field 785 may allow detailed information regarding the selected policy to be viewed and/or edited at field 786. The type of detailed information may be dependent on the type of insurance policy. For example, detailed information for a health insurance policy may include an insured party, and annual premium amount, a coverage amount, etc. Detailed information for a disability policy may include the insured party, an annual premium amount, a premium growth rate, an annual disability payout, a payout growth rate, etc. It will be appreciated that policies may be added to or removed from field 785 using add/remove buttons 783, or the select and drag methods described above. The premiums and potential payouts from insurance policies may be considered in forecasting the client's future financial condition.

FIGS. 20-22 show the interface 700, according to various embodiments, with the Goals button 719 selected. The user may use the screens shown in FIGS. 20-22 to view and/or edit financial goals of the client. Each goal may represent an expenditure or other financial event that the client would like to achieve in the future. Field 788 includes representations of potential goal types. For example, as shown in FIG. 21, field 788 includes representations for college education goals, pre-college education goals, home purchase goals, major expense goals, major purchase goals, and wedding goals. Field 790 shows representations of presently selected goals for the client. A goal may be added to field 790 by selecting the representation of the desired goal type from field 788 and using add/remove buttons 789, or by using the select and drag method described above.

Detailed information about current goals listed in field 790 may be viewed and/or edited at field 792 by selecting the representation of the goal from field 790. For example, the start date and the minimum and maximum costs of the goal may be entered and/or viewed. In various embodiments, the goal may be assigned a priority. For example, using slide-bar 795. The priority of the goal may be considered by the simulation module 112 as described herein. The funding source for the goal may also be viewed and/or edited, for example, by selecting button 794. The priority and funding source or sources for a goal may be considered by the simulation module 112 when simulations are conducted. Selecting button 794 may cause field 796 to appear, as shown in FIG. 21. Field 796 may include a field 804 including representations of assets available to the client to fund the goal, including loans. Selecting the representation of an asset or loan and actuating the add button 798 causes a representation of the asset to appear in field 802. This indicates that the asset will be used to fund the selected goal.

If a loan is selected as an asset for funding a goal, the field 791 may allow viewing and/or editing of detailed information about the loan, for example, as shown in FIG. 22. Field 793 may include information about fixed rate portions of the loan or loans, if any, including, for example, the annual interest rate, term, and repayment type. In various embodiments, field 795 (shown in FIG. 22A) may include information about variable rate portions of the loan or loans, if any, including, for example, the interest rate, spread, reset period, term, and repayment type.

In addition to, or instead of, the funding sources designated at field 796, it will be appreciated that the various simulations may implement an automatic funding hierarchy. For example, if there is not enough cash-on-hand to fund a year's expenditures (e.g., consumption, goals, etc.), the simulation may apply a set of funding rules. The funding rules may set forth a sequence for selling different types of assets and borrowing to finance expenditures. The funding rules may also specify a point at which further expenditure is disallowed (e.g., when credit is exhausted, or a predetermined amount of assets have been sold).

FIGS. 23-30 show the interface 700, according to various embodiments, with the Assumptions button 721 selected. The assumptions that may be edited or displayed may be parameters to be considered by the simulation module 112 to simulate the client's financial condition as described below. Data received through the interface 700 with the assumptions button 721 selected may be stored, for example, at assumptions database 116. As shown in FIG. 23, the interface includes a field 805 for viewing and/or editing various other assumptions. The field 805 may allow viewing and/or editing of various categories of assumptions. A category of assumptions may be selected from tab bar 804. It will be appreciated that various embodiments may omit some of the displayed assumptions, or add additional assumptions. In that case, tab bar 804 may list more, fewer, or different kinds of tabs, for example, as shown in FIGS. 25-30.

FIG. 23 shows the field 805, according to various embodiments, with the Portfolio Loss Tolerance tab 806 selected, allowing the user to view and/or edit the client's portfolio loss tolerance. The portfolio loss tolerance may be an indication of how much risk the client is willing to tolerate on their investment portfolio (e.g., a one year loss tolerance), and may be dynamic over the client's life. For example, a young individual client may be willing to take more risk than an older individual client who is nearing retirement. In various embodiments, the simulation module 112 may choose the assets that the client is assumed to buy and sell during the one or more simulated lives or business cycles based on the client's portfolio risk tolerance. For example, the simulation module 112 may choose a portfolio with a high concentration of equities for a highly risk tolerant client, or a bond-heavy portfolio for risk averse clients. In other various embodiments, the simulation module 112 may maintain a “fixed mix” asset allocation within a given percent (e.g., 5%) over the course of the client's life.

FIG. 24 shows the field 805, according to various embodiments, with the Asset Class Constraints tab 808 selected. The simulation module 112 may select the assets that the client is assumed to sell during the simulations in order to pay for certain expenses (e.g., goals, long-term care, etc.) based on the class constraints. In this way, the simulation module 112 can account for the asset allocation preferences of the client. Field 805 may show a series of corresponding columns 823, 824, 826. The column 823 lists asset classes that may be held by the client. The column 824 may include a row corresponding to each asset class listed in column 823. Each row lists the minimum amount of the corresponding asset class that the client wishes to hold as a percentage of the client's total portfolio. The column 826 may also include a row corresponding to each asset class listed in column 823. Each row in column 824 lists a maximum amount of the corresponding asset class that the client wishes to hold as a percentage of the client's total portfolio.

FIG. 25 shows the field 805, according to various embodiments, with the Borrowing tab 810 selected. The simulation module 112 may make assumptions as to whether and how much the client will borrow during the simulations based on the information entered at borrowing tab 810. The field 805 may include various other fields 828, 830, 832 for receiving and/or editing various information relating to whether the client will utilize loans, and, if so, what kinds of loans will be used. Field 828 allows the user to view and/or edit information regarding home equity loans. For example, the user may indicate whether home equity loans will be allowed, which property will be the underlying property for home equity loans, if allowed, and what interest rate will be assumed. For example, the interest rate may be entered as a base rate and spread. Field 830 allows the user to view and/or edit information regarding borrowing using margin loans. The user may indicate whether borrowing on margin is allowed in the generated financial models, and what interest rate will be assumed, as well as the periods over which interest will be calculated and paid. Field 832 allows the user to view and/or edit information regarding borrowing with qualified accounts. For example, the user may indicate whether borrowing with qualified accounts is allowed, and give an indication of what interest rate will be assumed.

FIG. 26 shows the field 805, according to various embodiments, with the Managed Account Fees tab 812 selected. The simulation module 112 may make assumptions regarding whether the client will own managed account shares during the simulations, and how much will be expended in doing so based on the information entered at managed account fees tab 812. The tab 812 allows the user to view and/or edit expected fees that will be charged to the client for managed accounts under the generated financial model. Default expenses may be stored, for example, at the assumption database 116. Column 834 lists asset classes. Column 836 may have a row corresponding to each of the asset classes listed in column 834. Each entry into column 836 may represent the fees associated with managed accounts including the corresponding asset class. As shown, the fees are listed as a percentage annual cost; however, it will be appreciated that any suitable measure may be used.

FIG. 27 shows the field 805, according to various embodiments, with the Salary Growth Rates tab 814 selected. The simulation module 112 may alter (e.g., raise or decrease) the value of the client's salaries, for example, as entered in tab 758 shown in FIG. 13, based on the assumptions entered at Salary Growth rate Tab 814. Default assumptions regarding salary growth rates may be stored in database 116. Referring to the tab 814, the field 805 includes a chart 838 allowing salary growth rates over various age ranges, for example, of the client to be viewed and/or edited. For individual clients, the tool 100 may assume, for example, that salary growth rates will be larger early in life than they are later.

FIG. 28 shows the field 805, according to various embodiments, with the Consumption Adjustment Tab 816 selected. The simulation module 112 may make adjustments to the client's household consumption during the simulations based on the information entered at the Consumption Adjustment tab 816. Default consumption adjustments may be stored, for example, at assumptions database 116. Fields 840 and 842 may allow the user to view and/or edit the default adjustments that the generated model will make to consumption in the event of contingencies. For example, field 840 lists the client's consumption during retirement as a percentage of previous consumption. Field 842 lists the consumption of the client's survivors, if the client were to pass away, as a percentage of previous consumption.

FIG. 29 shows the field 805, according to various embodiments, with the Tax Assumptions tab 818 selected according to various embodiments. The simulation module 112 may model the client's tax liability for each year included within a simulated time period (e.g., a life) based on the information entered at tab 818. Default assumptions regarding tax rates may be stored, for example, at assumptions database 116. With the tab 818 selected, the field 805 may allow the user to alter the default assumptions regarding taxation frameworks that the client will be subject to over the simulations. For example, table 844 shows income tax brackets and rates should the client file individually. Likewise, table 846 shows income tax brackets and tax rates should the client file jointly. In various embodiments, assumptions about capital gains tax rates and structure (not shown) may also be included. It will be appreciated that different tax information may be required in jurisdictions having other types of taxation in addition to, or instead of income taxation. Also, it will be appreciated when the client is a business unit, different tax information such as, for example, corporate rates, will be included.

FIG. 30 shows the field 805, according to various embodiments, with the Transaction Cost tab 820 selected. Default transaction costs for buying and selling securities may be stored, for example, at assumptions database 116. When the tab 820 is selected, the field 805 may allow the user to view and/or edit the default transactions costs that will be considered by the simulation module 112 in generating the model. Column 848 lists classes of assets that may be held by the client. Column 850 includes an entry corresponding to each of the asset classes listed in column 848 that sets forth the cost of buying the asset. For example, the cost may be listed as a percentage of the purchase or a flat fee. Column 852 also includes an entry corresponding to each of the asset classes listed in column 848. The entries in column 848 may indicate the cost of selling assets of the corresponding class. Again, the cost may be listed as a percentage of the purchase, or as a flat fee.

FIG. 31 shows the interface 700, according to various embodiments, including a Simulation Option field 854. The simulation option field 854 may allow the user to define parameters used by the financial modeling tool 100 to model the client's future financial conditions. For example, the number of simulations to be generated may be entered at field 856. In various embodiments, the default number of simulations may be 500. It will be appreciated that a minimum number of simulations, such as 500, may be required to generate a statistically robust result. Also, the economic world view over the forecasted time period may be entered at box 858. The world view may represent the user and/or client's assumptions about the general direction that the economy and markets will take in the future. This may affect the values of financial variables generated by the simulation module 112. Exemplary world views include bullish, bearish, and central. In other embodiments, different view settings and/or a different number of simulations may be used. Selecting the button 860 may activate the simulation module 112, causing the tool 100 to perform the simulations for the client.

FIGS. 32-46 show embodiments of the interface 900, according to various embodiments, configured to display graphical results of the simulations. The interface 900 may include a display field 902, a goal field 906 and a details field 908. The display field 902 shows a graphical representation, and in particular, the topographical chart described herein, representing the results of the model generated by the simulation module 112. The display field 902 may be updated in real time while simulations are being run, or may appear only after all simulations have been completed. Also, the display field 902 may display results for one financial output variable at a time, or the aggregate of multiple financial variables, and may be positioned on a pair of axes 912 and 914 defining a plane. Axis 912 represents time, and axis 914 represents the value of a financial variable or variables (e.g., net worth).

The values of the financial variables versus time generated over the various simulations may be aggregated and plotted on axes 912, 914, resulting in topographical chart 918. Each coordinate set on the axes 912, 914 corresponds to a point on the topographical chart 918. The height (or depth) of any particular point on the topographical chart indicates the number, or percentage, of simulations where the displayed financial variable (e.g., net worth) took the value and time (e.g., $1.5 million in 2021) of the corresponding coordinate set on axes 912, 914. Thus, in one embodiment, peaks on the topographical chart 918 represent outcomes with relatively high probability and topographical points below the peaks (including valleys) represent outcomes with relatively lower probabilities.

The chart 918 may also be color coded, with the color of a plotted point representing the frequency of the occurrence of its corresponding coordinate set. For example, the intensity of a color may indicate the frequency of occurrence (e.g., the probability) of its corresponding coordinate set. Points having colors that are more intense may have occurred in more simulations, while points having colors that are less intense may have occurred in relatively fewer simulations. In various embodiments, the color of points on the topographical chart 918 may also indicate the desirability (from the point of view of the client) of the corresponding coordinate sets. For example, points on the topographical chart 918 corresponding to undesirable coordinate sets (e.g., those indicating that the client lacks sufficient assets and/or income to maintain desired consumption levels, etc.) may be assigned one color, such as red, while points corresponding to desirable coordinate sets may be assigned another color, such as green or brown. It will be appreciated that this color coding may focus the client and/or user on the downside risks they face, and the choices they have to mitigate those risks. It will be appreciated that various shades of color or even additional colors may be used to illustrate gradations between degrees of desirability.

The legend 910 may allow the user to select which financial variable or variables are displayed in topographical chart 918. For example, the user may select a financial variable by actuating its corresponding button in legend 910. It will be appreciated that more than one financial variable at a time may be selected from legend 910 and viewed in field 902. In various embodiments, the legend 910 may be toggled on and off using Legend button 956. Also, the user may navigate the topographical chart 918, for example, using navigation buttons 916. By making the appropriate selection from buttons 916, the user may manipulate the axes 912, 914 of topographical chart 918 to thereby acquire different views of the chart 918, for example, as shown in FIGS. 33-35. Possible manipulations including, for example, linear translations, zoom in/out, rotation about multiple axes, and combinations thereof.

The interface 900 may also include various tools for examining the topographical chart 918. For example, a cursor 904 in FIG. 36 may be placed at any point on the topographical chart 918. In this embodiment, the cursor 904 corresponds to a line intercepting a point on the time axis 912 or a band encompassing multiple points and therefore, a period of time. FIG. 36 shows a state distribution window 926. In various embodiments, the state distribution field may be displayed when the user selects button 952. The state distribution window 926 displays a summary of the state of the client based on the calculated simulation outcomes at the time or period of time represented by the position of the cursor 904. This summary may help explain the events (e.g., in terms of simulations outcomes or otherwise) that are causing the displayed topographical outcome (e.g., the distribution of outcomes with respect to a particular variable or variables) at that time or period of time. For, example, the state distribution field 926 may show the number and/or percentage of local simulations where the client is dead, in ill-health, in long term care, in disability, and/or borrowing money at the cursor location. Again, the state of the client in any particular simulation may be determined based on input data stored, for example, in the assumptions database 116 and may be considered in generating values for the financial variables in a given simulation. The state distribution field 926 may also show the volatility of the client's portfolio over the simulations. In various embodiments, the interface 900 also includes a monthly histogram field 928, shown in FIG. 37. The monthly histogram field 928 may be displayed when the user selects button 954, and may show a distribution of a selected financial variable over all simulations at a given cursor location (e.g., time). In other words, the histogram field 928 may display a time cross-section of the topographical chart 918. Viewing the distribution of financial variable values in this way may help the user and/or client to understand the client's likely financial condition and plan accordingly. For example, if the selected financial variable is asset return for some or all of the client's assets, knowing the likely distribution of asset returns may help the client develop an appropriate hedging strategy. Also, if the selected financial variable is client borrowing, then insight can be provided regarding how much leverage risk the client is taking on. The location of the cursor 904, designated by a month and year, is displayed at field 905.

The simulation module 112 may also compute a likelihood of the client achieving desirable and acceptable levels of goal spend (e.g., the amount available to spend on a goal considering other goals and expenses) and the expected distribution of goal spend outcomes. The success or failure of each goal may be indicated at display field 902. For example, a representation or icon for each goal may be positioned along the time axis 912. The exemplary chart in FIG. 32 includes three goal representations 920, 922 and 924. The representations may be placed at positions corresponding to the start date for the goals. In various embodiments, each of the representations 920, 922, 924 may also include a number indicating the number and/or percentage of simulations in which the client achieves the respective goals. The representations 920, 922, 924 may also, or alternatively, be colored to indicate the number and/or percentage of simulations in which the client achieves the respective goals.

Selecting the representation 920, 922, 924 of a goal may cause additional detailed information about the goal to be displayed, as shown in pop-up field 921 in FIG. 38. Pop-up field 921 may include additional detailed information about goal 920 including, for example, the average amount that the client has available to spend on the selected goal in light of expenses and other goals (e.g., goal spend) the goal's priority, the goal's absolute minimum amount, the goals high-end target amount, and the client's success rate with the goal. Additional detailed information about the selected goal, in this case goal 920, may also be listed at details field 908. The details field 908 may include a chart 909, shown in more detail at FIG. 38A, that graphically displays the selected goal's absolute minimum amount 917, high-end target amount 919, and the distribution of amounts available for the goal over the simulations 923.

It will be appreciated that details of the selected goal may be modified at details field 908 and/or pop-up field 921. Also, the time horizon of the goal may be moved by selecting the representation for the goal and dragging it along the time axis 912. Additional goals may be added to the financial model, for example, by selecting a goal icon from field 906 and/or by selecting and dragging an icon from field 906 to field 902. It will be appreciated that different types of insurance, levels of borrowing and changes to asset allocation may also be added to the financial model. In other words, the client and/or user can test the implications of incurring different levels of risk in different ways (e.g., insuring or self insuring a risk; accepting a higher risk of failing to meet a goal versus taking more risk in the investment portfolio, etc.). It will be appreciated that adding additional goals, or modifying details and/or the time horizon of the selected goal causes the simulation module 112 to regenerate the simulations based on the modified goal. In that way, dynamic adjustments to the client's forecast can be achieved by modifying a goal.

FIG. 39 shows an embodiment of the interface 900 with the retirement goal 924 selected according to various embodiments. Pop-up field 925 shows detailed information regarding the success rate of the retirement goal. Success for the retirement goal may be measured by whether the client has sufficient income and/or assets to maintain their desired level of consumption after retirement. In various embodiments, the success or failure of the retirement goal may be judged by dividing the client's retirement into multiple bands. Each band may represent a block of years during the client's retirement. For example, in the embodiment depicted by FIG. 36, the client's retirement is divided into three bands, with the first band representing the first ten years of retirement, the second band representing the second ten years of retirement and the third band representing subsequent years of retirement. The simulation module 112 may calculate a success rate for each of the retirement bands, as well as a success rate for the retirement goal overall. If, during a simulation, the client has died before the start of a band then that simulation may not be included in the statistics for that band. If no lives live into a band then that band is not included in the determination of retirement success. The various bands of the retirement goal may also be shown on the plane formed by axes 912 and 914, for example, as bands 911, 913, 915. The success rate of each band may be indicated, for example, by its color.

It will be appreciated that the topographical chart 918 may be configured to display results for multiple financial variables simultaneously, if desired. For example, FIG. 39A shows a representation of the client's net worth 919 and liquid assets 921. In various embodiments, the financial variables displayed by the topographical chart 918 may be selected from drop-down menu 901. Different financial variables may be displayed in different colors. For example, in FIG. 39A, net worth 919 is shown in shades of brown, while liquid assets 921 are shown in shades of green.

In various embodiments, other chart types may be used in addition to or instead of the topographical chart 918. For example, FIG. 40 shows the display field 902 configured to display a line chart 927. The expected average value of the selected financial variables and/or variable (based on the simulation) at a point in time along the time axis 912 is indicated by the height (or depth) of the line chart 927. Also, FIG. 41 shows the display field 902 configured to show a step chart 929. The height (or depth) of the step chart 929 at a position on the time axis 912 may indicate the range (e.g., from maximum through minimum) of values of the selected financial variable has over the various simulations. The color of the step chart 929 may indicate the likelihood of values within the range. For example, the step chart 929 includes a line 931 indicating an average value for the displayed variable or variables. A series of colored bands extend upward and downward from the line 931, with the color of each band indicating the number of simulations resulting in values of the displayed financial variable or variables within the band. For example, in FIG. 41, bands with darker colors represent values of the displayed financial variable that were returned by relatively more of the simulations. FIG. 42 shows a step chart 930 similar to the step chart 929, but having dark lines separating the various colored bands. It will be appreciated that the results of the various simulations may be displayed according to any suitable graph or chart format.

The interface 900 may provide various additional options for manipulating the view and/or simulations. Referring to FIG. 32, selecting the Inflation Adjustment button 950 may cause the display field 902 to show results that are adjusted for the rate of inflation (i.e., the results may be displayed in constant or future dollars). Also, selecting Asset button 958 may cause a table of the client's initial assets to be displayed at an asset window 960 as shown in FIG. 43. In addition, it will be appreciated that the user may be able to make additional dynamic adjustments to the parameters and assumptions underlying the model of the client's financial condition. For example, the user may dynamically adjust the economic world view by selecting the world state menu 962 from the view menu of the interface 900 as shown, for example, at FIG. 44. Also, the user may adjust assumptions regarding the client or co-client's health by selecting health field 966 from the view menu of the interface 900, for example, as shown in FIG. 45. The user may also modify assumptions regarding the client's post-retirement consumption using drop-down menu 968, shown in FIG. 46. It will be appreciated that dynamically adjusting a parameter or assumption may cause simulation module 112 to recalculate the various simulations considering the modified parameter or assumption.

Embodiments of the present invention are also directed to apparatuses and methods for implementing a financial model. As described above, the financial model may generate a likely range of forecasted values of one or more financial variables describing a client over a given time period (e.g., the life of a client, the life of the client's household, etc.). Executing the financial model may involve generating a number of computer simulations of the time period. Each simulation may represent one simulated life of the client and, in various embodiments, may also include a simulated life of a member or members of the client's household, such as a spouse. For each simulated life, Monte Carlo methods may be used to estimate various health-related states of the client and resulting values for the financial variables over the course of the simulated life. The results of all simulated lives may be aggregated to generate an indication of the likelihood of various values of the financial variables into the future.

The financial model is described below as implemented by the computer system 110 described above, including simulation module 112. It will be appreciated, however, that the financial model may also be implemented by any other suitable computer system. Also, the financial model, as described below may receive input according to a user interface such as user interfaces 300 and 600 described above, or according to any other suitable user interface or interfaces. In addition, the financial model described below may present its output in the forms shown by user interfaces 600, 900 described above, or according to any other suitable forms.

FIG. 47 shows a process flow 4700, according to various embodiments, illustrating a method of generating a simulated life of a client and/or members of a client's household. The simulation may be set to begin at any point in the simulated life, including at birth. For example, if a forty-five (45) year old client is the subject of the financial model, then the simulation may be configured to begin with the client aged 45 years. At the outset of the simulation, the client may be assigned to a first state, for example, by the simulation module 112 (4702). In implementations where members of the client's household are also modeled, they may also be assigned to a first state. FIG. 48 shows a state diagram 4800 showing several exemplary states including, for example, a Healthy state 4802, a Long Term Care (LTC) state 4804, a Disabled state 4806, a Disabled in Long Term Care (Disabled in LTC) state 4810 and a Dead state 4808. The client may be initially assigned to one of the states 4802, 4804, 4806, 4808, 4810 based on user input. For example, if the client indicates that he or she is healthy, then he or she may initially be assigned to healthy state 4802.

The state of the client (and any modeled members of the client's household) may be successively recalculated, with each recalculation representing the passage of an interval or period of time in the simulated life. For example, each recalculation may represent the passage one month, one quarter, one year, etc. At each interval, the values of the financial variables may also be recalculated given the assets, income and expenses available to the client and considering the effects of the new state on expenses and income. In this way, the state of the client and its influence on the financial variables may be estimated at the various intervals throughout the simulated life. Steps 4704, 4706, 4708, 4710 and 4712 below illustrate one exemplary method of recalculating the clients state and the client's financial variables.

The simulation module 112 may calculate the probabilities of the client transitioning from his or her current state to some or all of the other allowable states (4704). According to the exemplary state diagram 4800 and assuming that the client is currently in the Healthy state 4802, this may involve calculating probabilities that the client will remain in the Healthy state 4802, that client will transition from the Healthy state 4802 to the LTC state 4804; that the client will transition from the Healthy state 4802 to the Disabled state 4806 and that the client will transition from the Healthy state 4802 to the Dead state 4808. In embodiments where other members of the client's household are also modeled, similar probabilities may also be found for these other members. Exemplary methods of calculating these probabilities for the client and any household members are discussed in more detail below.

When the probabilities are calculated, the simulation module 112 may randomly select a new state for the client, based on the calculated probabilities (4706). For example, if the probability of the client transitioning from the healthy state 4802 to the LTC state 4804 is 10%, then there may be a 10% chance that the simulation module 112 will randomly select the LTC state 4804 as the new state. Likewise, if there is a 50% chance that the client will remain in the healthy state 4802, then there may be a 50% chance that the simulation module 112 may randomly select the healthy state 4802 as the new state. New states may also be found in a similar way for other modeled members of the client's household, if any.

When a new state is determined for the client and for any other modeled members of the client's household, the simulation module 112 may calculate the consequences of the new state and new interval to the financial variables. For example, the simulation module 112 may calculate the client's income and assets given the new state and new interval (4708). The client's assets may carry over from a previous interval and may, according to various embodiments, be based on the assets provided as input to the financial model, as well as any assets accumulated during the simulated life due to interest, purchase, etc.

The client's income in the new interval may include any incomes from the client's salary, the salary of other household members, investments, etc. According to various embodiments, new income may initially be assigned to a cash account. The client's new state as well as the new states of any modeled household members may affect the amount of income available. For example, if the client, or the client's spouse, has transitioned into a disabled state, such as LTC state 4804, Disabled state 4806, or Disabled in LTC state 4810, then the affected party's income from salary may cease. In that case, provided that the client has appropriate disability or long term care insurance, the salary may be replaced with an insurance payment. If the client or client's household member has transitioned into the Dead state 4808, their income will also cease, however life insurance, if available, will be payable to the client's estate or surviving household members. Also, if the new interval indicates the onset of retirement for the client, then the client's salary income may cease and may be replaced with various pension/Social Security income, depending on availability and eligibility.

The simulation module 112 may also calculate the client's expenses at the new interval and state. According to various embodiments, expenses may be classified according to an expense hierarchy including discretionary and non-discretionary expenses. Non-discretionary expenses may include, for example, taxes, minimum levels of basic expenses, health care expenses, insurance premium expenses, etc. The amount of health care expense attributed to the client during each interval may be stochastically determined, for example, as described below. It will be appreciated that some non-discretionary expenses may depend on the new state. For example, if the client or a member of the client's household enters a disability state, such as LTC state 4804, Disabled state 4806 or Disabled in LTC state 4810, additional expenses may be necessary to maintain the client or household member. Discretionary expenses may include, for example, contributions to retirement accounts (which may be classified as discretionary or non-discretionary), contributions toward the client's goals, basic expenses above minimum levels, and other investments.

At each interval, the simulation module 112 may allocate the available income and assets to the new expenses. Income and assets may first be applied to non-discretionary expenses, and then to discretionary expenses. According to various embodiments, the amount of available income and assets may be determined according to a funding hierarchy. The expense hierarchy and funding hierarchy may be utilized together to match income and assets to current expenses. Any suitable hierarchies could be used. In one example, however, cash assets and current income (e.g., from the cash account) may be applied first to non-discretionary expenses. If any non-discretionary expenses remain then liquid assets may be utilized. If liquid assets are exhausted before non-discretionary expenses are met, then various loans may be used (e.g., home equity loans, mortgage loans, qualified account loans, etc.). Loans themselves may be prioritized according to any suitable method. Finally, if non-discretionary expenses are still not met, other measures may be implemented, such as, for example, credit card financing, liquidating of physical assets, and liquidating qualified (e.g., retirement) accounts.

According to various embodiments, funding options above a given point on the funding hierarchy may not be used to fund discretionary expenses. For example, although the simulation module 112 may simulate loans and asset liquidations to meet non-discretionary expenses, these funding options may not be used to fund discretionary expenses. According to various embodiments, an exception to this general practice may exist for goal funding. For example, the user may specify that certain types of loans may be used to finance goals, as described above with respect to FIGS. 22 and 22A.

According to various embodiments, the simulation module 112 may allocate available funding amount different goals at different levels. For example, prior to the target date, the simulation module 112 may begin a set-aside fund for each goal, based on the minimum and desired spend of the goal as well as the amount of time remaining between the current interval and the desired start date of the goal. For example, during each relevant interval, each goal may be expensed at two different levels. A first minimum level may represent an amount necessary to allow the client to meet a specified minimum goal spend. A second desirable level may represent an amount necessary to allow the client to meet a desired goal spend. Also, according to various embodiments, the user may have provided a priority for each goal, for example, as described above with respect to FIG. 20. The simulation module 112 may allocate any funds available for goal spending to the respective goal set-aside accounts based on any suitable method. For example, the simulation module 112 may first fund all of the goal set-asides at the minimum level in order of priority. If available funds still remain, then the simulation module 112 may allocate the remaining funds to raise the contributions to the goal set-asides to the desired level, again in order of goal priority.

According to various embodiments, the simulation module 112 may fund expenses directly from the cash account. Under some circumstances, it may be necessary for the simulation module 112 to rebalance the cash account. For example, if the cash account has a zero balance, the simulation module 112 may rebalance the account, by taking loans, selling assets, etc., for example, as set forth in the funding hierarchy. If all allowable loans and sales have been made, then the simulation module 112 may institute a crisis funding process, where long-term physical assets may be liquidated, for example, at reduced valuations. The cash account may also be rebalanced if its balance exceeds a given threshold (e.g., $10,000) or a given proportion of assets (e.g., if the cash account's forms a portion of total assets that is shifted by more than 500 bps). In these cases, the simulation module 112 may use the cash account funds to purchase assets according to an asset mix, which may be specified by the user or determined by the simulation module 112.

As shown by the process flow 4700, steps 4704, 4706, 4708, 4710 and 4712 may be continuously repeated until the client and all relevant members of the client's household reach the Dead state 4808. According to various embodiments, the simulation may end upon the deaths of the client and the client's spouse. Turning now to the exemplary state diagram 4800, the allowable states and state transitions will be examined. The Healthy state 4802 may represent a state where the client is in relatively good health. From the Healthy state 4802, four transitions are shown: 4850 to the LTC state 4804; 4852 to the Dead state 4808; 4854 to the Disabled state 4806; and 4856 back to the Healthy state. Each of the paths 4852, 4854, 4856 may have an associated probability representing the likelihood that a client will move along the respective path. For example, path 4850 between the Healthy state 4802 and the LTC state 4804 may be associated with the probability that the client will develop a need for long term care. The probabilities for each path may be taken and/or derived from an actuarial table, for example, as described below.

The LTC state 4804 may represent a state where the client is in need of long term care. This may be due to an injury, illness, etc. According to the exemplary state diagram 4800, a client in the LTC state 4804 is permitted to transition to the Healthy state 4802 along path 4858, to the Dead state along path 4860 or back to the LTC state 4804 along path 4862. The Disabled state 4806 may represent a state where the client has suffered a disability that prevents the client from working. From the Disabled state, the client may transition to the Disabled in LTC state 4810 along path 4861, to the Dead state 4808 along path 4864 or back to the Disabled state along path 4806. In the exemplary state diagram 4800, the Disabled state 4806 is assumed to permanent, hence no path is provided from the disabled state 4806 to the healthy state 4802.

The Disabled in LTC state 4810 may represent a state where the client is both disabled and in long term care. From the Disabled in LTC state 4810, the client may transition to the Disabled state 4806 along path 4868. In this case, the client may retain his or her disability, but may no longer require long term care. Also, from the Disabled in LTC state 4810, the client may transition to the Dead state 4808 along path 4872 or back to the Disabled in LTC state along path 4870. In the exemplary state diagram 4800, no transitions are allowed from the dead state 4808.

The exemplary state diagram 4800 shows just one set of allowable states and state transitions. It will be appreciated, however, that the allowable states and state transitions may vary based on the parameters of the financial model. For example, FIG. 49 shows another exemplary state diagram 4900 illustrating a financial model where an age of death for the client has been specified. Here, transitions to the Dead state 4808 are not allowed, and all paths to the Dead state 4808 have been omitted. In such a financial model, a simulated life may end when the simulated age of the client reaches the predetermined age of death.

The probabilities of transitioning between the various states may be taken from actuarial data and/or relationships. For example, a mortality rate may be used in determining the probability of progressing to the Dead state 4808 (e.g., along paths 4852, 4860, 4864 or 4872). According to various embodiments, the mortality rates used may be a function of age, sex and health status, although it will be appreciated that more dependencies may be found and utilized if desired. For any given client, sex may be specified by the input data. Age may be an indication of temporal position within the simulated life. The health status used to find the mortality rate for any given client may be determined according to various methods. For example, it may be determined based on the state of health reported by the client and may also depend on the clients state. For example, a client in the Disabled state 4806 may not exist in the same state of health as a client in the Healthy state 4802.

According to various embodiments, a correction factor may be applied to the mortality rate to adjust for increases in life expectancy that occur with time. For example, a set of correction factors may be derived. Each correction factor may correspond to an age of the client. The actual mortality rate may then be found, for example, according to Equation 1 below:

M=Mu×(1−F)<t>  (1)

In Equation 1, M represents the actual mortality rate; Mu represents the unadjusted mortality rate, F represents the age-specific adjustment factor; and t represents length of time between the time at which the mortality rate is being found and the present time.

A long term disability rate may be used in determining the probability of transitioning to the Disabled state 4806 (e.g., along path 4854). Like the mortality rates, the long term disability rate for any given client may be a function of various factors including, for example, the client's age, sex and health status. Several long term care (LTC) related rates may be used in determining the probabilities of entering and exiting LTC state 4804 and Disabled in LTC state 4810. For example, an LTC incidence rate may described the probability that a client will enter LTC state 4804 and/or Disabled in LTC state 4810. The LTC incidence rate may be a function of various factors including, for example, marital status, age and health status. Other relevant LTC related rate is the LTC persistence rate and the LTC exit by death rate. The LTC persistence rate may describe the probability that a client in LTC will remain in LTC. This rate may be used to find the probabilities of transitioning along paths 4850 or 4862. According to various embodiments, the LTC persistence rate may be a function of age and the duration of the client's stay in the LTC state 4810 or 4804. For example, a client who has been in LTC for an extended period of time may be less likely to leave LTC. The LTC exit by death rate may describe the chance that when the client leaves an LTC state 4804 or 4810 by death, or returns to another state. The LTC exit by death rate may be used, for example, in conjunction with the LTC persistence rate, to determine the probabilities that a client will transition along paths 4860 or 4872.

As described above, morbidity, or the rate of healthcare spend, is another expense that may be considered by the financial model. According to various embodiments, morbidity may be characterized as a given amount of spend over a given period of time. This period of time may be chosen to correspond to the state recalculation interval described above. In this way, incorporating morbidity into the financial model may involve adding the calculated morbidity to the total expenses for each interval. According to various embodiments, morbidity may be expressed as a function of, for example, age, sex and health status. For example, morbidity may be represented as a set of health care spend levels, with each level associated with a probability that a person of a given age, sex and health status would incur healthcare related expenses of up to that level over the given period of time. The actual morbidity used at any given point in the financial model may be found by randomly selecting a spend level, given a particular client. For example, if actuarial data suggests that 1.08% of healthy males between the ages of 45 and 49 should expect to incur monthly healthcare expenses of $905, then approximately 1.08% of all clients existing as healthy men aged 46-49 would experience morbidity resulting in expenses of $905.

As used herein: the term, “client” refers to an individual or household that is the subject of a financial modeling tool; and the term, “user” refers to an operator of the financial modeling tool. In various embodiments, the user may also be a client or an employee of a client. In other non-limiting embodiments, the user may be a financial advisor providing advice to the client.

As used herein, “storing” when used in reference to a computer or computer system refers to any suitable type of storing operation including, for example, storing a value to memory, storing a value to cache memory, storing a value to a processor register, storing a value to a non-volatile data storage device, etc.

As used herein, a “computer” or “computer system” may be, for example and without limitation, either alone or in combination, a personal computer (PC), server-based computer, main frame, server, microcomputer, minicomputer, laptop, games console, personal data assistant (PDA), cellular phone, pager, processor, including wireless and/or wireline varieties thereof, and/or any other computerized device capable of configuration for processing data for standalone application and/or over a networked medium or media. Computers and computer systems disclosed herein may include operatively associated memory for storing certain software applications used in obtaining, processing, storing and/or communicating data. It can be appreciated that such memory can be internal, external, remote or local with respect to its operatively associated computer or computer system. Memory may also include any means for storing software or other instructions including, for example and without limitation, a hard disk, an optical disk, floppy disk, ROM (read only memory), RAM (random access memory), PROM (programmable ROM), EEPROM (extended erasable PROM), and/or other like computer-readable media.

The various modules 108, 112 of the system 110 may be implemented as software code to be executed by a processor(s) of the system 110 or any other computer system using any type of suitable computer instruction type. The software code may be stored as a series of instructions or commands on a computer readable medium.

While several embodiments of the invention have been described, it should be apparent that various modifications, alterations and adaptations to those embodiments may occur to persons skilled in the art with the attainment of some or all of the advantages of the present invention. It is therefore intended to cover all such modifications, alterations and adaptations without departing from the scope and spirit of the present invention as defined by the appended claims. 

We claim:
 1. A method of graphically representing the consequences that different financial choices have on financial outcomes, using a graphical user interface generated by a computing device, the method including the following processor-implemented steps: (a) representing multiple goals as graphical icons in a 2D or 3D environment; (b) graphically representing various choices or decisions that affect the likelihood of one or more user-selected or defined goals being realized or not realized, where a choice or a decision relating to one such goal affects the likelihood of realizing or not realizing one or more other such goals; (c) enabling a user to input a choice relating to one or more user-selected or defined goals; (d) using a simulation or calculation tool to calculate the likelihood of each user-selected or defined goal being realized or not realized, given the choice input by the user; (e) graphically representing in the 2D or 3D environment the likelihood of each user-selected or defined goal being realized or not realized.
 2. The method of claim 1 including the following processor-implemented steps: (a) graphically enabling a user to input a new choice relating to one or more goals; (b) using the simulation or calculation tool to calculate the likelihood of each goal being realized or not realized, given the new choice input by the user; (c) graphically representing in the 2D or 3D environment the likelihood of each goal being realized or not realized.
 3. The method of claim 1 including the following processor-implemented steps: (a) enabling a user to select a specific graphical icon and to drag the icon on a chart with time as an x-axis at the date when the goal is to be realised; (b) using a simulation or calculation tool to calculate the likelihood of that goal being realized at the specified time.
 4. The method of claim 1 including the following processor-implemented steps: (a) displaying a financial goal as a graphical icon in a menu or array of graphical icons, each representing a different goal; (b) enabling a user to add additional goals, or modify details and/or the time horizon of the selected goal, in order to cause a simulation or calculation engine to regenerate simulations based on the modified goal, and hence enable a dynamic graphical representation of the consequences of different financial choices.
 5. The method of claim 1 including the following processor-implemented steps: (a) enabling a user to define or position a goal on a chart with time as an x-axis at the date when the goal is to be realised; (b) using a simulation or calculation tool to calculate the likelihood of that goal being realised; (c) graphically representing the likelihood of that goal being realized; (d) enabling a user to alter a variable, such as the date when the goal is to be realized, or its priority, or alter any other parameter impacting that affects the likelihood of that goal being realised; (e) using the simulation or calculation tool to re-calculate the likelihood of that goal being realized; (f) graphically representing the new likelihood of that goal being realized.
 6. The method of claim 1 including the following processor-implemented steps: (a) displaying a financial goal as a graphical icon in a menu or array of graphical icons, each representing a different goal; (b) displaying a menu of different risk-related options that relate to the risk of realizing that goal; (c) using a simulation or calculation tool to calculate the likelihood of that goal being realised, taking into account the risk-related options; (d) graphically representing the likelihood of that goal being realized.
 7. The method of claim 1 including the following processor-implemented steps: (a) displaying a financial goal as a graphical icon; (b) using a simulation or calculation tool to calculate the likelihood of that goal being realized; (c) colour-coding the graphical icon depending on that likelihood.
 8. The method of claim 1 including the following processor-implemented steps: (a) displaying a financial goal as a graphical icon; (b) using a simulation or calculation tool to calculate the likelihood of that goal being realized; (c) graphically representing the likelihood of that goal being realized by setting the height of the icon above a time axis on a graph.
 9. The method of claim 1 including the following processor-implemented steps: (a) displaying a financial goal as a graphical icon; (b) using a simulation or calculation tool to calculate the likelihood of that goal being realized; (c) superimposing each over a graphical representation of the user's net worth, each goal graphically representing the likelihood of it being realized.
 10. The method of claim 1 including the following processor-implemented steps: (a) graphically representing factors, risks or conditions which are likely to cause the goal to be missed, such as disability, long term illness, long term care, death, macro-economic factors such as financial shocks.
 11. The method of claim 1 including the following processor-implemented steps: enabling the user to model assets and liabilities of a household or an individual or a group of individuals and to graphically represent that model in a GUI shown on a single page or display screen.
 12. The method of claim 1 including the following processor-implemented steps: (a) graphically enabling the user to understand the actions needed to increase the chance of realizing a goal by presenting different selectable options that, if selected, lead to the simulation or calculation tool to re-calculate the likelihood of that goal being realized.
 13. The method of claim 1 including the following processor-implemented steps: (a) graphically enabling the user to understand why the chance of realizing a goal is low by including a graphical explanation that can be opened by the user.
 14. The method of claim 1 including the following processor-implemented step: (a) when the user selects an icon representing a goal, then the step of graphically displaying information about the goal.
 15. The method of claim 1 in which the simulation tool uses a Monte Carlo simulation.
 16. The method of claim 1 where the goal is selected from the list of the following goals: retirement; a major holiday; buying a house; financing college education; getting married. 